Triple

T23898097
Position Surface form Disambiguated ID Type / Status
Subject Cassie Bowden E600960 entity
Predicate majorStoryEvent P148591 FINISHED
Object wakes up next to a dead passenger in a Bangkok hotel room LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: wakes up next to a dead passenger in a Bangkok hotel room | Statement: [Cassie Bowden, majorStoryEvent, wakes up next to a dead passenger in a Bangkok hotel room]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: majorStoryEvent
Context triple: [Cassie Bowden, majorStoryEvent, wakes up next to a dead passenger in a Bangkok hotel room]
  • A. significantEvent
    Indicates that an event involving the entities is of notable importance or impact within a given context.
  • B. notableStoryEvent chosen
    Indicates that an event plays a significant or memorable role within the narrative or storyline associated with the subject.
  • C. significantEventType
    Indicates the specific category or kind of major or noteworthy event associated with an entity or situation.
  • D. significantEventInvolves
    Indicates that a significant event includes or engages a particular entity as a participant or key element.
  • E. isMajorEventOf
    Indicates that an event is a primary, significant, or defining occurrence within the context of another entity (such as a project, period, or process).
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e295341ac0819080647f2908af793c completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cddb3fdc819096dc84a1774d9bee completed April 29, 2026, 9:22 a.m.
PD Predicate disambiguation batch_69f1614e24b48190a1c8fb5b7c75ee0f completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 8:25 p.m.